CLOUD COMPUTING Essentials of K CHANDRASEKARAN CLOUD COMPUTING Essentials of CLOUD COMPUTING Essentials of K Chandrasekaran CRC Press Taylor & Francis Group 6000 Broken Sound Parkway NW, Suite 300 Boca Raton, FL 33487-2742 © 2015 by Taylor & Francis Group, LLC CRC Press is an imprint of Taylor & Francis Group, an Informa business No claim to original U.S Government works Version Date: 20141014 International Standard Book Number-13: 978-1-4822-0544-2 (eBook - PDF) This book contains information obtained from authentic and highly regarded sources Reasonable efforts have been made to publish reliable data and information, but the author and publisher cannot assume responsibility for the validity of all materials or the consequences of their use The authors and publishers have attempted to trace the copyright holders of all material reproduced in this publication and apologize to copyright holders if permission to publish in this form has not been obtained If any copyright material has not 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and are used only for identification and explanation without intent to infringe Visit the Taylor & Francis Web site at http://www.taylorandfrancis.com and the CRC Press Web site at http://www.crcpress.com Contents Foreword xvii Preface xix Computing Paradigms Learning Objectives Preamble 1.1 High-Performance Computing 1.2 Parallel Computing 1.3 Distributed Computing .3 1.4 Cluster Computing 1.5 Grid Computing 1.6 Cloud Computing 1.7 Biocomputing .5 1.8 Mobile Computing .6 1.9 Quantum Computing 1.10 Optical Computing 1.11 Nanocomputing 1.12 Network Computing 1.13 Summary .8 Key Points Review Questions Further Reading Cloud Computing Fundamentals .9 Learning Objectives Preamble 2.1 Motivation for Cloud Computing 10 2.1.1 The Need for Cloud Computing .11 2.2 Defining Cloud Computing 12 2.2.1 NIST Definition of Cloud Computing 12 2.2.2 Cloud Computing Is a Service 13 2.2.3 Cloud Computing Is a Platform 13 2.3 5-4-3 Principles of Cloud computing 14 2.3.1 Five Essential Characteristics 14 2.3.2 Four Cloud Deployment Models 15 2.3.3 Three Service Offering Models 16 2.4 Cloud Ecosystem 17 2.5 Requirements for Cloud Services 19 2.6 Cloud Application 21 2.7 Benefits and Drawbacks 22 v vi Contents 2.8 Summary 24 Review Points 24 Review Questions 25 Reference 25 Further Reading 26 Cloud Computing Architecture and Management 27 Learning Objectives 27 Preamble 27 3.1 Introduction 28 3.2 Cloud Architecture 28 3.2.1 Layer (User/Client Layer) 28 3.2.2 Layer (Network Layer) 29 3.2.3 Layer (Cloud Management Layer) 30 3.2.4 Layer (Hardware Resource Layer) 30 3.3 Anatomy of the Cloud .30 3.4 Network Connectivity in Cloud Computing 32 3.4.1 Public Cloud Access Networking 32 3.4.2 Private Cloud Access Networking 32 3.4.3 Intracloud Networking for Public Cloud Services 32 3.4.4 Private Intracloud Networking 33 3.4.5 New Facets in Private Networks 33 3.4.6 Path for Internet Traffic 34 3.5 Applications on the Cloud 34 3.6 Managing the Cloud 37 3.6.1 Managing the Cloud Infrastructure 37 3.6.2 Managing the Cloud Application 39 3.7 Migrating Application to Cloud 40 3.7.1 Phases of Cloud Migration 40 3.7.2 Approaches for Cloud Migration 41 3.8 Summary 41 Review Points 42 Review Questions 42 References 43 Further Reading 43 Cloud Deployment Models 45 Learning Objectives 45 Preamble 45 4.1 Introduction 46 4.2 Private Cloud 47 4.2.1 Characteristics 47 4.2.2 Suitability .48 4.2.3 On-Premise Private Cloud 49 4.2.3.1 Issues 49 vii Contents 4.2.4 Outsourced Private Cloud 51 4.2.4.1 Issues 51 4.2.5 Advantages 52 4.2.6 Disadvantages 52 4.3 Public Cloud 53 4.3.1 Characteristics 53 4.3.2 Suitability .54 4.3.3 Issues 54 4.3.4 Advantages 56 4.3.5 Disadvantages 56 4.4 Community Cloud 56 4.4.1 Characteristics 57 4.4.2 Suitability 58 4.4.3 On-Premise Community Cloud 58 4.4.3.1 Issues 58 4.4.4 Outsourced Community Cloud 59 4.4.4.1 Issues 60 4.4.5 Advantages 60 4.4.6 Disadvantages 61 4.5 Hybrid Cloud 61 4.5.1 Characteristics 62 4.5.2 Suitability 62 4.5.3 Issues 62 4.5.4 Advantages 63 4.5.5 Disadvantages .64 4.6 Summary .64 Review Points 64 Review Questions 65 References 65 Cloud Service Models 67 Learning Objectives 67 Preamble 67 5.1 Introduction 68 5.2 Infrastructure as a Service 71 5.2.1 Characteristics of IaaS 72 5.2.2 Suitability of IaaS 73 5.2.3 Pros and Cons of IaaS 74 5.2.4 Summary of IaaS Providers 75 5.3 Platform as a Service 77 5.3.1 Characteristics of PaaS 79 5.3.2 Suitability of PaaS 80 5.3.3 Pros and Cons of PaaS 81 5.3.4 Summary of PaaS Providers 83 viii Contents 5.4 Software as a Service 83 5.4.1 Characteristics of SaaS 86 5.4.2 Suitability of SaaS 87 5.4.3 Pros and Cons of SaaS 88 5.4.4 Summary of SaaS Providers 90 5.5 Other Cloud Service Models 90 5.6 Summary 93 Review Points 94 Review Questions 94 Further Reading 95 Technological Drivers for Cloud Computing 97 Learning Objectives 97 Preamble 97 6.1 Introduction 98 6.2 SOA and Cloud 98 6.2.1 SOA and SOC 99 6.2.2 Benefits of SOA 100 6.2.3 Technologies Used by SOA 101 6.2.4 Similarities and Differences between SOA and Cloud Computing 101 6.2.4.1 Similarities 102 6.2.4.2 Differences 102 6.2.5 How SOA Meets Cloud Computing 103 6.2.6 CCOA 104 6.3 Virtualization 105 6.3.1 Approaches in Virtualization 106 6.3.1.1 Full Virtualization 106 6.3.1.2 Paravirtualization 106 6.3.1.3 Hardware-Assisted Virtualization 107 6.3.2 Hypervisor and Its Role 107 6.3.3 Types of Virtualization 108 6.3.3.1 OS Virtualization 108 6.3.3.2 Server Virtualization 108 6.3.3.3 Memory Virtualization 108 6.3.3.4 Storage Virtualization 108 6.3.3.5 Network Virtualization 109 6.3.3.6 Application Virtualization 109 6.4 Multicore Technology 109 6.4.1 Multicore Processors and VM Scalability 110 6.4.2 Multicore Technology and the Parallelism in Cloud 110 6.4.3 Case Study 110 6.5 Memory and Storage Technologies 111 6.5.1 Cloud Storage Requirements 111 358 Essentials of Cloud Computing Another issue with interoperability is that the service providers not allow the users to use products or components of other vendors in their cloud infrastructure Thus, a user has to use the components given by one cloud provider only There are two possible reasons for this problem One is that the vendors not want to lose their customers, and so they not allow them to use other vendor’s components or to migrate to other vendors Another is that there is very less technical support or there is very less advancement in this area, so even if the cloud components are open source or are not governed by any such policy or rule, there is very less chance that two clouds would be interoperable Interoperability and portability go hand in hand There are three aspects of portability, namely application portability, platform portability, and infrastructure portability Thus, if the portability issues are resolved, then it would not take much time to make the clouds interoperable as there are only a few more issues that need to be considered other than portability All the aforementioned problems are due to one primary reason, and that is standardization The main problem with the cloud service providers is that they not have a common standard for all the cloud service providers Each service provider follows their own standards, but these standards vary from company to company Thus, no two companies have the same standards According to a report by Carnegie Mellon University (CMU), there are different aspects of standardization on each service model of cloud There are three basic service models of cloud: Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS) The standardization will affect all the three models in a different manner According to CMU, the SaaS models would be the least benefitted by the standards This is because such software involves licensing terms, and standardization would not have a greater effect on it Similarly, PaaS also may not be that much benefitted from the standardization models But, IaaS would have a considerable amount of benefits as the workloads or resources are in the form of VMs and storage disks, and if standardization is made, then the users can migrate their VMs from one service provider to another There is a lot of effort being put by different organizations to make standards There have been several attempts by several communities to have interoperable systems and to m aintain the standards [6] This process will continue in the future, and the day is not far when interoperability would be the property of every cloud service provider 14.6 Cloud Governance Governance is a term in the corporate world that generally involves the process of creating value to organization by creating strategic objectives that will lead to growth of the company and will maintain a certain level of control Advanced Concepts in Cloud Computing 359 over the company Governance is not to be confused with management Both terms, though similar, have lot of difference Governance comes into picture where there is a booming industry that involves a lot of resources including people Governance involves maintaining and following certain policies throughout the company These involve high-level decision making that would affect all the people related to the company Cloud computing is one of the rapidly growing technologies Almost all the big companies have started using cloud As the days go by, cloud is becoming bigger and vast Not only computing resources but also the number of people working in cloud is increasing Hence, there is a necessity of governance mechanism to maintain the growth of cloud There is a need to regulate all the resources such that the people involved or affected by the cloud directly or indirectly are benefitted and all the things that happen through the cloud are being monitored properly Cloud governance is very important because it is a known fact that well-governed organizations have a higher probability of sustaining business and retaining their position in the industry If governed properly, an organization is able to adapt to the changes quickly Cloud governance involves certain hurdles There are several responsibilities involved in cloud governance, which include some of the points by He [7]: Quality of service: Quality of service is another major issue as far as an organization is concerned There are no standard metrics or a standard way to ensure the quality of service to the customers There are several models or algorithms that are proposed to ensure the quality of service to the users Service-level agreements (SLA) are the major parameter that is considered for assuring QoS These SLAs are considered to be very important Negotiations are made between the cloud service provider and the cloud user based on these SLAs An SLA gives flexibility to the cloud user, and a cloud user can claim or demand justice or compensation if SLA terms are violated in any way by the service provider Thus, it is the responsibility of the service provider to ensure that the SLA terms are satisfied at any cost Complying with the laws and standards: This is one of the most difficult parts as far as cloud is concerned As the back-end servers, storage disks and VMs are spread all over the world there are lots of issues being raised because of the data stored in the cloud The problem comes when people from one country try to access the data stored in another country The laws of both the countries may vary Hence, coming to a conclusion on which law should be applied to which user and eventually what should be the standard law for the company is very difficult 360 Essentials of Cloud Computing Adapt to changing service mechanisms: There are different service mechanisms involved in delivering services Time to time, these service mechanisms change and the service provider should have the capability to adapt to different service mechanisms as quickly as possible Data privacy issue: The laws related to data privacy had been an issue for a long time The data of the user stored should not be viewed by any outsider or even the service provider There is no surety on whether the data details stored by the user are safe Thus, this is one of the most important issues that need to be resolved Multitenancy: Multitenancy is a property of cloud that involves sharing of workspace (instance) by many users (clients) It is one of the important properties of cloud that made it popular Though it is good, it has some issues to security A user can break the security barrier and can access others’ data, as all the users share a single system Giving security to the user is still an issue that needs to be addressed Governance inside the organization (internal): The rules inside the organization for people related to cloud projects should be given As these projects are large and complex, the rules should be specified clearly The number of people working on cloud and the number of resources being used for cloud in a company are very high Hence, there needs to be a law related to these issues, that is, the way to use these resources should also be defined Based on the these issues, researchers have proposed some governance models like the Lifecycle Governance model and the Lewam Woldu Cloud Governance model As cloud governance is similar to governance in serviceoriented architecture (SOA) and thus both of them are considered as the subset of IT governance This area is one of the emerging areas There are several aspects of governance that can be automated, and several companies have come up with a tool for cloud governance These tools include cloud governance tool by Dell tool name Agility platform by service mesh etc An active research is going on in this area, and companies and researchers are coming up with several models and tools for governance 14.7 Computational Intelligence in Cloud According to Andries P Engelbrecht, computational intelligence (CI) is the study of adaptive mechanisms to enable or facilitate intelligent behavior in complex and changing environments These mechanisms include those artificial intelligence (AI) paradigms that exhibit an ability to learn or adapt to new situations, generalize, abstract, discover, and associate [8] An important aspect of CI Advanced Concepts in Cloud Computing 361 is adaptivity This field exists for nearly four decades Scientists have been using these algorithms for solving different kinds of problems CI is basically used for problems that cannot be solved by using conventional algorithms There are many real-time problems that cannot be solved using conventional methods, and in these cases, some practical natural approaches prove to be a better choice CI includes all the heuristic algorithms that are inspired by natural processes Some of the popular examples are genetic algorithm and swarm optimization Genetic algorithms come under the subdivision called evolutionary algorithms These evolutionary algorithms are inspired by evolutionary process of the living being Similarly, swarm optimization also comes under this category Swarm optimization techniques are inspired by fish school or bird flocks, that is, their group behavior property is used Artificial immune system is one of the methods based on our immune system Similarly, there are several other methods that are based on natural processes These computational methodologies are extensively used for optimization-related problems This approach has an extensive use in cloud computing Cloud computing in simple terms is offering service (resources) to the customers It involves a lot of resources at the back end Managing resources is a difficult task This resource management involves several important tasks like resource scheduling, provisioning, consolidation, and migration Some of the aforementioned tasks like scheduling cannot have exhaustive methods The prime ways of scheduling resources are workflow scheduling and task scheduling Scheduling problem as such is a nondeterministic polynomialtime hard (NP-hard) problem NP-hard problems are difficult problems that not have an exhaustive solution and can only have approximate solutions So for these kinds of problems, optimization techniques such as CI algorithm can be used Optimization techniques are usually characterized by properties that give good approximate solutions that are near to the correct solution The aforementioned are some of the instances These algorithms consume less amount of time than the exhaustive search algorithms The more the problems become complex, the more are the chances of using CI algorithms Advantages • Suitable for complex problems for which exhaustive search is not possible • Consumes less time than the exhaustive counterpart 14.8 Green Cloud Data centers are the backbone of cloud computing The data centers housing the clouds often use up a lot of energy Data centers are the facility that houses computer systems and their related components The power 362 Essentials of Cloud Computing consumed by data centers mainly constitutes of the power required to run the actual equipment and the power used up by devices to cool the equipment To cool the systems in the data center, we usually make use of precision air conditioners that control the temperature and humidity throughout the day and can also be managed remotely As more and more people switch to cloud computing, the energy consumed by it becomes significant In an era of great concern for a greener environment, this area in cloud computing should also be considered It is from this basic need that green cloud computing arose Green cloud computing is basically the computing solutions to the problem of energy consumption These solutions also aim at reducing the OPerational EXpenses (OPEX) The increase in operational costs reduces the marginal profit of cloud service providers The power consumption of data centers also has a nonnegligible impact on the increase in carbon emissions and global warming Thus, there is a need to develop energy-efficient solutions to cloud computing For this, an in-depth analysis of power efficiency of clouds needs to be done (Figure 14.9) The architecture of data centers is of different types such as two tier and three tier In all these architectures, energy efficiency has to be analyzed The data center efficiency is usually calculated by considering the performance delivered per watt We have two metrics: Power usage effectiveness (PUE): It compares the energy used for computing against the energy used for cooling and other overhead The ideal value is 1.0 It can be calculated as PUE = Total facility energy IT equipment energy The lowest PUE that has been achieved in the present scenario is 1.13 in Google data center Data center infrastructure efficiency (DCiE): This is the reciprocal of PUE: DCiE = PUE Green solution Application/user Reduced energy and increased revenue Cloud datacenter FIGURE 14.9 Green cloud computing (Adapted from Garg, S.K and Buyya, R., Green cloud computing and environmental sustainability, in Harnessing Green IT: Principles and Practices, S Murugesan and G.R Gangadharan (eds.), 2012, pp 315–340.) Advanced Concepts in Cloud Computing 363 Studies have shown that idle servers consume around 66% of energy compared to their fully loaded configuration The management of memory modules and other factors contribute to this energy consumption Thus, we can save a considerable amount of power if the workloads are concentrated on a minimum number of the computing servers, thus enabling the shutting down of idle servers Basically, the different power management techniques in computer architecture are as follows: Dynamic voltage scaling (DVS): Increasing or reducing the voltage in a component Dynamic frequency scaling (DFS): This is also called CPU throttling, where the frequency of the microprocessor is adjusted so as to save power or to lessen the amount of generated heat Dynamic shutdown (DNS): This scheme selectively shuts down the idle or underutilized components The green lining in cloud computing is provided by virtualization Virtualization is creating a virtual entity Using virtualization, multiple users can be accommodated on a single host If there was no virtualization, each user would have to be allocated separate physical machines This can be avoided by creating isolated virtual entities for each user on the same physical machine Thus, virtualization is a tool for efficient utilization of resources It can also serve as a tool for energy saving Workload consolidation and server consolidation can be used to reduce energy consumption When servers are overloaded, the VMs on the server can be transported to other underloaded servers If there are many underloaded servers, the VMs can be consolidated to one or more servers, enabling the idle servers to be switched off There are various simulators to simulate the cloud computing environment But not many of them measure the energy efficiency of cloud To tackle this issue, the GreenCloud Simulator was developed in 2013 by a team led by Dzmitry Kliazovich at the University of Luxembourg It provides a finegrained simulation of energy-efficient clouds [10] The simulator focuses on the communication between the various elements in the cloud This approach is adapted as more than 30% of the total energy is consumed by the elements for communication There are various works in the literature that fall under the area of green cloud computing There are energy-efficient scheduling strategies that make use of VM migrations Green routing aims to provide routing service in an energy-efficient manner Green networking is the area that focuses on energyefficiency issues in networking Another notable work in this area is the GreenCloud Architecture proposed by Garg and Buyya [9] They propose a framework that curbs the energy consumption of clouds They propose architecture with an intermediate layer called the GreenBroker This GreenBroker makes use of a directory that contains the carbon emission details of various 364 Essentials of Cloud Computing cloud providers so as to provide the greenest provider to the customer at the same time maximizing the profit The carbon emission information of various cloud providers at IaaS level is measured by using energy meters At the PaaS level, energy profiling tools are used The energy-saving strategies for data centers can be divided into four broad sections: Energy-efficient techniques for servers Energy-efficient techniques for network Energy-efficient techniques for servers and network Cooling and renewable energy Under the fourth category, a notable work has been done by Baikie and Hosman [11] where an attempt is made to reduce the energy used by data centers This includes methods such as using renewable energy to power the data centers and so on 14.9 Cloud Analytics Cloud analytics is a process of doing any business or data-intensive analysis (data analytics) in public or private cloud Data analytics is a process of examining unprocessed or raw data to make some meaningful conclusion from the data The results may include either a value or a set of values or a graph Data analytics has been very popular Several researchers all over the world are using this technique effectively, and based on the results, important decisions are taken If it is done on large amount of data that can be in the range of terabytes and petabytes, it is called as big data analytics Big data analytics has been a recent buzzword in the industry Nowadays, almost the entire world is using the Internet, and the amount of data that are generated per day is very large There are several places and several companies that analyze some parts of these data to get a meaningful conclusion For example, a social networking site can be considered Usually, the numbers of users of a social networking site are large Suppose the site administrator wants to analyze the users according to the game in which they are interested, he or she can that by analyzing their whole data based on one or more parameters that determine or estimate the results There are several other places apart from the Internet where a large amount of data are generated, and these data require a complete analysis For example, if an insurance company wants to find out the best customer and wants to rate their customers based on their monthly payments, they can this by using analytics Similarly, there are several applications of data analytics Advanced Concepts in Cloud Computing 365 Analyzing a small amount of data is easy, but when the amount of data is increased, it becomes difficult The data analytics operation that is done in today’s world is on data that are in terabytes and petabytes For doing this kind of data-intensive operations, heavy back-end resources, and most importantly high-processing power, are needed This would cost companies or organizations a lot The companies or organizations sometimes cannot afford to buy that many resources, as buying and maintaining it are a big issue In this case, there is no other option left for the organization other than renting the resources There had been situations before when this kind of power was needed For example, the Large Hadron Collider (LHC), which was used by CERN, recorded the data in petabytes per week and there was a necessity to process these data The scientists did not have their own resources, so they relied upon the grid technology for the resources The grid computing model is one of the computing technologies that allow the user to use the large number of resources on a pay-per-use basis This technology is primarily intended for research organizations to use the vast processing resources available These resources were provided for a fee, and primarily these were used for high-end scientific applications in areas of astronomy, physics, bioinformatics, etc These are sometimes called utility grids and are considered as the reason for the success of many high data-intensive projects Similar to grid, cloud can also be used for renting resources Cloud computing is a computing model where primarily resource, softwares, and platforms are offered as services There is a major difference between grid and cloud computing Unlike grid, cloud services are divided into several types In this context, two major types are private and public Public cloud offers services to all the people around the globe, whereas private cloud is restricted and can only be used by an organization or individual When the private or public cloud is used for data analysis, then it is called cloud analytics Cloud analytics is very popular as it is analogous to grid platform and has an advantage that anybody in the world can use this platform for doing analytics People can use these public or private cloud services for analyzing the huge amount of data, and they can pay according to what they use; there is no need to buy any resource This is very useful for companies in real time, because these can be used whenever it is necessary, that is, only when it is required and there is no necessity to maintain any hardware resources Figure 14.10 depicts the classification of cloud analytics Another aspect of cloud analytics is that instead of using the private cloud or public cloud as such, people can use the cloud applications that are built in the cloud and that are designed specifically for data analysis Thus, instead of using resources directly, the delivery model called SaaS is used Here, cloud-based software is created by the provider and the user can analyze the data by using the software, which is usually a web application This kind of cloud application will allow the user to use any kind of device that can access a simple web application 366 Essentials of Cloud Computing SaaS Cloud-based data analytics applications PaaS IaaS Cloud-based general applications FIGURE 14.10 Cloud analytics 14.10 Summary This chapter briefly described the advanced topics in cloud computing The topics that were included are related to recent advancements in this field All the topics that are discussed have a potential impact The topics either are important as an application or have certain research importance The topics that were discussed briefly were mobile cloud, intercloud, media cloud, interoperability and standards, cloud governance, green cloud, cloud analytics, and impacts of CI in cloud computing and cloud management All the aforementioned topics are discussed with illustrations on the benefits of each technology and their impact on the industry or academia Review Points • Federation: Federation of clouds is the deployment and management of multiple cloud computing services to match business needs (see Section 14.1) Advanced Concepts in Cloud Computing 367 • Multicloud: Multicloud involves two or more cloud service providers (see Section 14.1) • Peer-to-peer intercloud federation: This is one of the types of cloud federation where there is no central entity (see Section 14.1) • Centralized intercloud federation: This is a type of cloud federation that involves a central entity (see Section 14.1) • Precision air conditioners: These are the type of air conditioners used for cooling in data centers (see Section 14.8) • OPerational EXpenses (OPEX): OPerational EXpenses is the ongoing cost for running a product, business, or system (see Section 14.8) • Dynamic voltage scaling (DVS): This is the process of dynamically adjusting the voltage levels used in a data center (see Section 14.8) • Dynamic frequency scaling (DFS): This involves dynamically varying the frequency of the microprocessor (see Section 14.8) • Dynamic shutdown (DNS): This is a power management technique where idle servers are shut down (see Section 14.8) • Server consolidation: This is the process of reducing the number of underutilized servers (see Section 14.8) • Cloudlet: A cloudlet can be basically viewed as a mini data center (see Section 14.3) • Vendor lock-in: In vendor lock-in problem, the cloud service provider does not allow the users to migrate to other cloud (see Section 14.5) • Cloud analytics: Cloud analytics is a process of doing any business or data-intensive analysis (data analytics) in public or private cloud (see Section 14.9) • Multitenancy: Multitenancy is a property of cloud that involves sharing of workspace (instance) by many users (clients) (see Section 14.6) • Data analytics: Data analytics is a process of examining unprocessed or raw data to make some meaningful conclusion from the data (see Section 14.9) Review Questions What are the different types of intercloud topologies? What are the differences between multicloud and federation of clouds? Enumerate the various advantages of intercloud 368 Essentials of Cloud Computing What are the different techniques for power management in computer architecture? Give an outline of the energy-saving strategies for data centers Define the metrics used to measure the data center efficiency Discuss the different scenarios where MCC can be employed What are the major issues in multimedia cloud? What is the need for cloud management? 10 Why standardization is necessary? 11 What are the advantages of using CI in cloud? 12 Explain vendor lock-in problem 13 Why cloud governance is necessary? 14 What are the two ways of using cloud analytics? 15 What is an SLA? References http://computersight.com/software/cloud-computing-chapter-one-reviewand-guide/ Accessed March 23, 2013 http://2.bp.blogspot.com/ Accessed March 23, 2013 http://cloudstrategypartners.blogspot.in/2013/04/intercloud-not-all-samefederation.html http://www.cse.wustl.edu/~jain/cse574–10/ftp/cloud/index.html Accessed February 24, 2014 Poehlein, S., V Saxena, G T Willis, J Fedders, and M Guttmann Moving to the media cloud Available [Online]: http://h20195.www2.hp.com/V2/GetPDF aspx/4AA2–1000ENW.pdf (accessed August 15, 2010) The role of standards in CloudComputing interoperability Available [Online]: https://resources.sei.cmu.edu/asset_files/TechnicalNote/2012_004_001_ 28143.pdf Accessed February 24, 2014 He, Y The lifecycle process model for cloud governance, 2011 Engelbrecht, A P Computational Intelligence: An Introduction, 2nd edn Wiley Publications Garg, S K and R Buyya Green cloud computing and environmental sustainability In S Murugesan and G R Gangadharan (eds.), Harnessing Green IT: Principles and Practices 2012, pp 315–340 10 Kliazovich, D., P Bouvry, and S U Khan GreenCloud: A packet-level simulator of energy-aware cloud computing data centers The Journal of Supercomputing 62(3): 1263–1283, 2012 11 Baikie, B and L Hosman Green cloud computing in developing regions Moving data and processing closer to the end user Telecom World (ITU WT), 2011 Technical Symposium at ITU, Geneva, Switzerland, October 24–27, 2011, pp. 24–28 Advanced Concepts in Cloud Computing 369 Further Reading Gupta, P and S Gupta Mobile cloud computing: The future of cloud International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering (IJAREEIE) 1(3), September 2012 Fernando, N., S W Loke, and W Rahayu Mobile cloud computing: A survey Future Generation Computer Systems 29(1): 84–106, 2013 Cloud Incubator While Paper – DMTF, A White Paper from the Open Cloud Standards Incubator http://us.cdn4.123rf.com/168nwm/ Computer Science & Engineering Cloud computing—accessing computing resources over the Internet—is rapidly changing the landscape of information technology Its primary benefits compared to on-premise computing models are reduced costs and increased agility and scalability Hence, cloud computing is receiving considerable interest among several stakeholders—businesses, the IT industry, application developers, researchers, and students To successfully embrace this new computing model, these stakeholders need to acquire new cloud computing skills and knowledge This book is designed to provide readers with a clear and thorough understanding of the key aspects of cloud computing Presented in an easy-to-understand style, Essentials of Cloud Computing begins with an introduction to basic cloud computing concepts It then covers cloud computing architecture, deployment models, programming models, and cloud service types, such as Software as a Service (SaaS) and Infrastructure as a Service (IaaS) It also discusses the cloud’s networking aspects, major service providers, open source support, and security issues The book concludes with a discussion of several advanced topics, such as mobile clouds, media clouds, and green clouds This book is intended for beginners as well as experienced practitioners who want to learn more about cloud computing It includes many case studies, programming examples, and industry-based applications Each chapter concludes with review questions that help readers check their understanding of the presented topics Essentials of Cloud Computing will help readers understand the issues and challenges of cloud computing and will give them the tools needed to develop and deploy applications in clouds Features • Presents a complete picture of cloud computing using real-life examples • Looks at the hardware, software, and networks of the cloud from a service-oriented perspective • Covers the engineering aspects of designing cloud applications and the technological aspects of using cloud applications • Includes details of both open source and proprietary products and services K21449 w w w c rc p r e s s c o m ... CLOUD COMPUTING Essentials of CLOUD COMPUTING Essentials of K Chandrasekaran CRC Press Taylor & Francis Group 6000 Broken Sound Parkway NW, Suite 300 Boca Raton,... look into the various computing paradigms: namely high performance computing, cluster computing, grid computing, cloud computing, bio -computing, mobile computing, quantum computing, optical computing, ... Motivation for Cloud Computing 10 2.1.1 The Need for Cloud Computing .11 2.2 Defining Cloud Computing 12 2.2.1 NIST Definition of Cloud Computing 12 2.2.2 Cloud Computing Is